reference deployment

Headend System Simulator on AWS

Collect and centralize smart-meter data

This solution deploys Headend System Simulator to the Amazon Web Services (AWS) Cloud. It's for utility companies that want to centralize smart-meter data and provide users a RESTful API to securely retrieve smart-meter readings using real-time or batch-based processing. This solution launches a time-series database to collect and store smart-meter data, a REST API for retrieving data, and a Secure Shell (SSH) File Transfer Protocol (SFTP) service to host batch-data files.


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This solution was developed by AWS.

  •  What you'll build
  • This solution sets up the following:

    • An Amazon API Gateway readings resource with GET method that returns paginated smart-meter readings.
    • Four AWS Lambda functions to do the following:
      • Query Amazon Timestream and return paginated results to utility supplier.
      • Insert asynchronous file request messages using a POST method into an Amazon Simple Queue Service (Amazon SQS) queue and update the status in an Amazon DynamoDB table.
      • Return the details of file requests to utility supplier using a GET method.
      • Query Timestream for number of records requested to pass right-sized parameters to an AWS Glue job.
    • An Amazon SQS queue that invokes a worker Lambda function.
    • An AWS Glue job that does the following:
      • Uses a Java Database Connectivity (JDBC) driver to connect to Timestream.
      • Combines query results into a single file and uploads to the meter readings Amazon Simple Storage Service (Amazon S3) bucket.
      • In the DynamoDB table, marks the file request status as complete and record the location of the results file in the meter readings S3 bucket.
    • A Timestream database and table that contains utility smart-meter readings.
    • An S3 bucket that contains the readings files exported by AWS Glue.
    • AWS Transfer for SFTP (AWS SFTP) to transfer meter readings files.
    • AWS Secrets Manager to store the private certificate used by AWS SFTP.
    • (Optional) The Device Data Generator Partner Solution to generate and insert simulated smart-meter readings into Amazon Timestream at regular intervals. (not shown)
  •  How to deploy
  • To deploy this solution, follow instructions in the deployment guide, which includes these steps.

    1. Sign in to your AWS account. If you don't have an AWS account, sign up at
    2. Install the latest version of Docker Desktop.
    3. Launch the solution. The stack takes about 5 minutes to deploy. Before you create the stack, choose the AWS Region from the top toolbar.
    4. Follow the postdeployment steps.
    5. Test the deployment.
  •  Costs and licenses
  • You are responsible for the cost of the AWS services and any third-party licenses used while running this solution. There is no additional cost for using the solution.

    This solution includes configuration parameters that you can customize. Some of these settings, such as instance type, affect the cost of deployment. For cost estimates, refer to the pricing pages for each AWS service you use. Prices are subject to change.

    Tip: After you deploy a solution, create AWS Cost and Usage Reports to track associated costs. These reports deliver billing metrics to an Amazon Simple Storage Service (Amazon S3) bucket in your account. They provide cost estimates based on usage throughout each month and aggregate the data at the end of the month. For more information, refer to What are AWS Cost and Usage Reports?